# Wbiplot: Weighted Biplot In analytics: Regression Outlier Detection, Stationary Bootstrap, Testing Weak Stationarity, NA Imputation, and Other Tools for Data Analysis

## Description

`Wbiplot` produces a biplot with any weight distribution between Row and Column markers. This way the full spectrum from perfect row resolution (Row-metric preserving biplot) to perfect column resolution (Column-metric preserving biplot) is available.

## Usage

 `1` ```Wbiplot(df, numer1, denom1 = 1, numer2, denom2 = 1, cx = 0.5) ```

## Arguments

 `df` a dataframe with numeric values only `numer1` numerator of first exponent (can be a decimal) `denom1` denominator of first exponent (default: 1) `numer2` numerator of second exponent (can be a decimal) `denom2` denominator of second exponent (default: 1) `cx` graphical magnification factor (default: 0.5)

## Details

This function makes use of function `Matpow` from package powerplus to be able to raise any valid matrix (see `Matpow` documentation) to any real power between 0 and 1 included.

## Value

A biplot of a dataframe with the specified weights. Weights can either be supplied as two fractions, or as two decimal numbers.

## Author(s)

`Matpow`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16``` ```require(graphics) # Exemple 1: Row metric preserving Wbiplot(USArrests, numer1 = 1, numer2 = 0, cx = 0.6) # Exemple 2: Column metric preserving Wbiplot(USArrests, numer1 = 0, numer2 = 1, cx = 0.6) # Comparison with function \code{biplot} from package \pkg{stats} biplot(princomp(USArrests), cex = 0.6) # Example 3: Custom, 50-50 Wbiplot(USArrests, numer1 = 0.5, numer2 = 0.5) # Example 4: Custom, 20-80 Wbiplot(USArrests, numer1 = 0.2, numer2 = 0.8) ```